title: Protein contact map prediction using committee machine approach.
abstract: Protein contact map is a simplified representation of a protein's spatial structure. The Committee Machine is a machine learning method that allots the learning task to a number of learners and divides the input space into subspaces. Learners' responses to an input are combined to produce the system's final response, which is more accurate than any single individual's response. In this study, we propose a novel method called CMP_model, for contact map prediction based on the committee machine. The results of the proposed model in comparison with two other models, show considerable gain (an accuracy improvement from 0.05 to 0.15).
authors.affiliation: Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran. nhabibi@ec.iut.ac.ir
authors.forename: Narjeskhatoon
authors.initials: N
authors.lastname: Habibi
authors.forename: Mohamad
authors.initials: M
authors.lastname: Saraee
authors.forename: Hassan
authors.initials: H
authors.lastname: Korbekandi
mesh_terms: D001185:Artificial Intelligence; D001665:Binding Sites; D008958:Models, Molecular; D011487:Protein Conformation; D017510:Protein Folding; D060066:Protein Interaction Maps; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins